Child Development, xxxx 2013, Volume 00, Number 0, Pages 1–11
Forces and Motion: How Young Children Understand Causal Events
Tilbe Göksun
Nathan R. George and
Kathy Hirsh-Pasek
University of Pennsylvania
Temple University
Roberta M. Golinkoff
University of Delaware
How do children evaluate complex causal events? This study investigates preschoolers’ representation of force
dynamics in causal scenes, asking whether (a) children understand how single and dual forces impact an
object’s movement and (b) this understanding varies across cause types (Cause, Enable, Prevent). Three-and-a
half- to 5.5-year-olds (n = 60) played a board game in which they were asked to predict the endpoint of a ball
being acted upon by one or two forces. Children mostly understood the interactions of forces underlying each
type of cause; only 5.5-year-olds could integrate two contradictory forces. Children perceive force interactions
underlying causal events, but some concepts might not be fully understood until later in childhood. This
study provides a new way of thinking about causal relations.
Consider the everyday events of an ordinary playground: children throwing Frisbees, blocking soccer
balls, and helping each other push their friends on
the swing. Psychologists tend to describe these
complex scenes with simple causal mechanisms
(Michotte, 1963) or chains of simple causes (e.g., Baillargeon, 1994; Cohen, Rundell, Spellman, & Cashon,
1999; Leslie, 1982, 1984; Oakes & Cohen, 1990; Rakison & Krogh, 2012; Saxe, Tenenbaum, & Carey, 2005;
Saxe, Tzelnic, & Carey, 2007). In this article, we move
beyond this simple Michottean causality and examine how children process complex causal scenes in
light of force dynamics theory. Defined as the interaction between entities in space resulting from multiple forces (Talmy, 1988; Wolff, 2003, 2007), force
dynamics encompasses not only simple cause–effect
relations but also ways in which two or more forces
This work was supported by NICHD Grant 5R01HD050199
and by NSF Grant BCS-0642529 to the second and third authors.
We thank everyone at the Temple University Infant Lab and in
the Spatial Intelligence and Learning Center (particularly the
RISC group at Temple University) for their invaluable contributions to this project. We also thank Nora Newcombe for helpful
suggestions on many phases of this project. Special thanks to
Kelly Fisher, Sarah Roseberry, Andrea Frick, Wendy Shallcross,
Yannos Misitzis, Russell Richie, Katrina Ferrara, Carolyn
Winslow, and Rhea Miles for their help in stimulus design, data
collection, and coding. We are grateful to the children and
parents who participated in the study.
Correspondence concerning this article should be addressed to
Tilbe Göksun, Department of Neurology, University of Pennsylvania, 3400 Spruce Street, 3 Gates, Philadelphia, PA 19104.
Electronic mail may be sent to tilbe@mail.med.penn.edu.
can affect the trajectory of an entity in an event.
Drawing on Wolff’s (2003, 2007) force dynamics theory of causal language, we investigate the development of force dynamics representations in children
and reconsider the psychologist’s definition of causality given the complexity of the causal relations
that constitute everyday events.
Force Dynamics
Until recently, force dynamics has been “a
neglected field of study” (Talmy, 1988) in semantics,
as well as in spatial understanding, event perception,
and language development. Event perception
research has traditionally emphasized the perception
of causality from a Michottean perspective (Michotte,
1963), relying on direct causal events in which one
object (i.e., agent) contacts a stationary object (i.e.,
patient), causing the patient to immediately move
along the agent’s trajectory while the agent ceases
movement. The spatiotemporal contiguity between
the two movements creates the perception of causality. Evidence for the primacy of spatiotemporal
features in causal perception has yielded promising
results with both adults (e.g., Choi & Scholl, 2006;
Fugelsang, Roser, Corballis, Gazzaniga, & Dunbar,
© 2013 The Authors
Child Development © 2013 Society for Research in Child Development, Inc.
All rights reserved. 0009-3920/2013/xxxx-xxxx
DOI: 10.1111/cdev.12035
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Göksun, George, Hirsh-Pasek, and Golinkoff
2005; Schlottmann, Ray, Mitchell, & Demetriou,
2006) and infants (e.g., Carey, 2009; Cohen & Amsel,
1998; Leslie & Keeble, 1987; Muentener & Carey,
2010; Newman, Choi, Wynn, & Scholl, 2008; Oakes,
1994; Rakison & Krogh, 2012; Saxe et al., 2005; Saxe
et al., 2007; Shultz, 1982). Many have used such findings to support a mechanist account of causal perception, in which the transmission of some physical
quantity (e.g., energy, momentum) is considered necessary and sufficient for the perception of causal
interactions (see Shultz, 1982).
While such conclusions might reflect a valid part
of causal knowledge, they are limited with respect
to the full array of causal interactions. Other factors
relevant to the interpretations of complex causal
events have not been explained. For example, a
vital component of a causal event, the spatial array
of forces (e.g., the angle of an object’s movement
after collision), has recently been shown to be influential to causal perception in adults (Straube &
Chatterjee, 2010; Wolff, 2007). Moreover, previous
research has focused primarily on one-force causal
interactions, yet the environment often contains
multiple kinetic forces working in concert. Extending the analysis of causality into these more complicated scenarios may reveal a greater range of
development in these representations.
Building on work by Talmy (1985, 1988) and Jackendoff (1990), a recent theory addresses the limitations of previous mechanist accounts of causality
(Wolff, 2003, 2007). The force dynamics model makes
improvements on previous research by taking into
account the multiple forces that underlie the full
array of causal events. Force dynamics expands our
view of cause, distinguishing among the types of
cause: Cause (one force that moves an object), Enable
(a secondary force that promotes motion in the
intended direction), and Prevent (a secondary force
that hinders motion in the intended direction; Wolff,
2003). (We choose “enable” rather than “help” to be
in accord with the force dynamics literature; e.g.,
Sloman, Barbey, & Hotaling, 2009; Wolff, 2003,
2007.) For example, when a boat is moving toward a
port, a secondary force, “the wind,” might prevent
the boat from doing so by changing its direction. In
contrast, if the boat were hit by a ship moving in the
intended direction, the force of the ship would enable
the boat to reach port. Wolff and colleagues found
that adults correctly map causal verbs onto events
through the identification of these three event classes
(Cause, Enable, and Prevent), supporting the theory
that causality has different category-level representations (Wolff, 2003, 2007; Wolff & Song, 2003; Wolff,
Song, & Driscoll, 2002). It appears that these causal
categories are codified in a number of languages. For
example, Wolff, Klettke, Ventura, and Song (2005)
showed that English, German, Russian, Spanish, and
Arabic all use verbs to express Cause, Enable, and
Prevent relations. The authors concluded that these
expressions of causal relations are not unique to
English. Here, we borrow Wolff’s terminology of the
force dynamics of causal language and adjust it to
assess preschool children’s perception of forces and
their interactions in complex causal scenes.
Understanding an Object’s Trajectory and Integrating
Forces in Childhood
Infants in their 1st year of life expect motion
events to have causes (e.g., Harding & Golinkoff,
1979) and have some knowledge of an object’s trajectory in such events, even when a portion of the
object’s path is occluded (Johnson et al., 2003; Kotovsky & Baillargeon, 2000; Muentener & Carey, 2010;
Spelke, Philips, & Woodward, 1995). Yet preschool
children often have misconceptions about the trajectories of an object’s motion when causal forces are
combined. For example, 4.5- to 5.5-year-old children
predicted a straight path rather than a parabolic
trajectory when asked to combine momentum and
gravity to judge the path of a ball rolling off a table
or dropping from a moving train (Kaiser, McCloskey, & Proffitt, 1986; Kaiser, Proffitt, & McCloskey,
1985; but see Hood, 1995, 1998). Moreover, research
has shown that even older children have trouble integrating forces to estimate the movement of an object
and consequently the result of an event. For example,
Pauen (1996) presented elementary schoolchildren
(ages between 6 and 10 years) a task in which two
forces acted on a target object. The target object was
fixed at the center of a circular platform, surrounded
by a barrier with an opening. This barrier could be
rotated around the platform. Each force was represented by different number of weights resting
on small plates connected to the target object by
separate cords. In each trial, the experimenter manipulated the number of weights on the plates (magnitude) and the angle between the cords (direction).
Children were asked to rotate the barrier to position
the opening such that the target would slide through
it. Results showed that children younger than
10 years of age seemed to ignore one aspect of the
vectors—either magnitude or direction. One intriguing exception is preschool children’s reasoning about
the path of a ball exiting a curved tube. Five-year-olds
correctly solve this common physics problem, predicting a straight path for the ball; however,
following entry into school, children begin attributing
Forces and Motion
a curved path to the ball, suggesting that such early
reasoning is not the robust, sophisticated reasoning
seen in adults (Kaiser et al., 1986). Such fallacies
about the relations between force and motion persist
even into high school (e.g., McDermott & Redish,
1999; Roth, 1990).
To this point, research on force dynamics in
childhood has mostly been restricted to knowledge
of intuitive physics and nonverbal causal reasoning
(for a review, see Wilkening & Cacchione, 2011).
However, there is value in also examining how
force dynamics is manifested both in event representations and in the corresponding semantic categories of language that both go beyond simplistic
pictures of causality. Recent evidence suggests that
before producing motion verbs such as cross or
jump, children detect the components of motion
events (e.g., the trajectory of the movement, the figure of the action, the manner of the figure). That is,
they acquire the necessary conceptual basis before
they lexicalize different types of events in languages
(Göksun, Hirsh-Pasek, & Golinkoff, 2010b). Similar
conclusions can be drawn about the development
of simple causal language.
As Wolff et al. (2005) suggested, many languages represent these complex events in their
causal language system. Developmental research
has shown that children start using causal verbs
such as break and cut in the 2nd year of life, but it
is not until age 4 years that they reliably use
causal verbs and other causal connectives to
describe causal relations (Bowerman, 1974; Clark,
2003; Göksun, Hirsh-Pasek, & Golinkoff, 2010a).
Interestingly, 4- and 5-year-olds rely on gestures to
supplement their speech before they form complete
causal sentences. For example, these children
represent the instrument of a causal relation only
in gesture without mentioning it in speech
(Göksun et al., 2010a). Thus, the productive use of
causal language lags behind the understanding of
simple causes.
According to one view, learning to use different
types of causal verbs (Cause, Enable, and Prevent)
to talk about causal scenes that integrate various
forces requires that children understand complex
causal events. Wolff’s (2007) study with adults suggests some characteristics that these representations
may contain. His research has shown that the representations of force dynamics underlying language
encode both the direction and the magnitude of
forces working in concert. Alternatively, exposure
to verbs that encode Cause, Enable, and Prevent,
may encourage children to attend to complex, multiforce events. In other words, although simple
3
causal language may be based on early concepts,
learning causal language might help children to
move from this basic understanding of causal relations to force dynamic representations (for arguments on a different domain-learning number
words and counting, see Lipton & Spelke, 2005).
Thus, the examination of children’s understanding
of multiple force events sets the stage for determining whether these representations are precursors to
force dynamics verbs or whether these semantic
categories enhance children’s representations of
these events.
The Current Study
Force dynamics defines different classes of causal
events and verbs according to different patterns of
forces. To make these distinctions among causal
events, children must be able to combine and integrate multiple forces. The current state of the field
is not clear on whether young children can combine
and integrate multiple forces before they productively talk about complex causal relations (Clark,
2003). This study examines how preschoolers evaluate multiple forces and process events in terms of
force dynamics. We ask three questions: First, do
children between 3.5 and 5.5 years of age understand the impact of one and two forces on an
object’s movement and its endpoint? Based on the
findings of Pauen (1996), we hypothesize that younger children might be unable to integrate two forces
to predict the movement of an object. Second, are
children’s predictions equally accurate among the
different types of cause (Cause, Enable, Prevent)?
We predict that children might represent Cause and
Enable relations earlier than Prevent relations,
because Prevent involves two contradictory forces.
Finally, what types of errors do children make
when trying to integrate forces? We analyze children’s errors for each categorical representation to
see whether children perseverate on a single force,
despite the presence of other forces.
Method
Participants
The final sample consisted of 60 monolingual
English-speaking children, balanced for gender and
evenly separated into three age groups: 3.5-yearolds (M = 44.64 months, SD = 2.67, range = 40.02–
48.08 months), 4.5-year-olds (M = 54.95 months,
SD = 3.94, range = 49.06–60.21 months), and 5.5year-olds (M = 64.86 months, SD = 2.36, range =
4
Göksun, George, Hirsh-Pasek, and Golinkoff
61.17–71.0 months). Children were predominantly
White and of middle-class families from a Northeastern city in the United States. Based on prior research
on children’s understandings of other physical problems (e.g., Kim & Spelke, 1999), and children’s effective use of causal language (e.g., Göksun et al.,
2010a), these age groups were chosen to represent
the complete developmental trajectory for force
dynamics. Additional data from five 3.5-year-olds
and one 4.5-year-old were excluded from analysis
due to failure to respond during the task (six). In
addition, data from one child from each of the older
groups were discarded due to experimenter error
(two). Finally, nine adults (M = 28.77 years,
SD = 4.91) were recruited to assess adults’ performance on this novel task.
Materials
Children’s understanding of causal relations was
examined through an interactive board game. The
game board (180 cm 9 180 cm) was made of a
green felt mat and divided into a 6 9 6 grid of
30 cm 9 30 cm squares using masking tape (see
Figure 1). A 1.5-in. diameter curved plastic tube
(16 in. tall 9 5 in. deep) was inserted into a model
house so that it entered into the roof and exited out
from the front. In all conditions, the first force was
provided by the motion of a small foam ball exiting
the tube. In Enable and Prevent relations, the hairdryer’s “wind” was used as a secondary force. There
were also four colored felt squares (30 cm 9 30 cm).
The child was asked to choose the one they liked for
marking the final location of the ball. The board
was laid on the ground in a quiet room where each
child was tested individually. A camera recorded
the session for later coding.
Procedure
The experiment consisted of two test phases (oneand two-force trials). Each test phase started with
a practice trial. The order of the phases (one- and
two-force trials) remained constant among children.
One-force trials: Practice trial. First, the experimenter presented the task materials and described the
game to the child (see Figure 1, top row). Next, the
experimenter asked the child to pick her favorite
colored square and explained the child’s role in the
game: “The goal of the game is to guess where the ball
will stop. You are the player and will guess where the
ball goes and stops on these squares.” Then, the house
was put on one of the board’s grid squares, with the
end of the tube in line with the edge of the next
square. The experimenter drew the child’s attention to
the tube saying, “Wow, do you see the long chimney
and how it goes through the house and comes out the
side?” Finally, the experimenter took the ball and held
it over the top of the tube, asking the child where she
thought the ball would exit and how far it would
travel. After the child put the colored square on the
felt mat, the experimenter said, “Watch what happens
when I drop the ball from here (the top of the tube).
Did you see how it goes? See how it came out from
here (showing the curved part of the tube—the door
of the house)?” Next, the experimenter asked the child
to drop the ball from the tube so that the child was
familiar with the procedure and the weight of the ball.
After being familiarized with the task materials,
the experimenter placed the house on a different
square and asked the same question as before, now
requiring the child to put the colored square (the
same size as one of the grid squares) on the grid
square where she thought the ball would land.
The child was permitted to place the colored
square anywhere, including locations off the board,
although such responses were not encouraged from
the outset. The child was asked to step aside and
told to watch where the ball stopped. The experimenter dropped the ball from the chimney and the
ball stopped on the board. If the child was incorrect, the experimenter would encourage the child to
try again and would repeat the action one more
time. The practice trial ensured that the child was
familiar with the materials and attuned to the
movement of the ball with one force. If a child
failed in the second practice trial, the experimenter
explained the procedure one more time and
ensured that the child understood the task by asking the child to point at the end state of the ball.
One-force trials: Test trials. Phase 1 of the test
contained three simple Cause trials, in which the
experimenter was the only cause of the action (oneforce trials). The house was placed in different positions and turned in either horizontal or diagonal
directions as shown in Figure 1. By manipulating
the orientation of the house, we examined whether
children’s integration of forces was dependent on
any specific spatial orientation. The child either
received two horizontal trials and one diagonal trial
or two diagonal trials and one horizontal trial in a
counterbalanced order. For each location, the child
made a prediction using the colored square and the
experimenter dropped the ball through the tube.
Two-force trials: Practice trial. This phase started
by introducing the child to the workings of the
hairdryer that served as the second force (i.e., the
wind) on the ball. The child felt the “wind” by
Forces and Motion
5
Figure 1. The board game setup with the model house, hairdryer, and materials (top row) and sample Cause, Enable, and Prevent trials
(one- and two-force trials). The yellow arrows represent the direction of the ball exiting the model house (initial force) and the red
arrows represent the direction of the hairdryer (secondary force). In prevent trials, the left picture is the “opposing” Prevent and the
right picture is the “perpendicular” Prevent. See the online version of this article for Figure 1 in color.
turning the hairdryer on and placing his or her
hand close to the opening. Then, the experimenter
put the ball in front of the hairdryer on the mat
and turned the hairdryer on to show the child that
the wind from the hairdryer moved the ball on the
mat. After this introduction and ensuring that the
child was still engaged in the game, the house and
the hairdryer were positioned on the board for a
practice trial. The hairdryer was lined up flush to
the middle of the left edge of the square in front
(15 cm) of the fort, with the wind blowing across
the front of the house. The experimenter turned on
the hairdryer and then rested his hand on top of
the tube. Then, the child was asked where the ball
would land and to put his or her colored square on
the grid. After the child placed his or her colored
square, the experimenter dropped the ball through
the tube. The child was again asked to step aside
and told to watch where the ball stopped. If a child
was incorrect, the experimenter would encourage
the child to try again and repeat the action one
more time. The experimenter always ensured that
the child followed where the ball landed by asking
the child to point at the end state of the ball. In this
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Göksun, George, Hirsh-Pasek, and Golinkoff
second practice trial for two forces, the experimenter confirmed that the child saw the movement
of the ball with the second force.
Two-force trials: Test trials. One Cause trial with
the hairdryer, two Enable trials, and two Prevent
trials were presented in a counterbalanced order
using the same script as above. In the new Cause
trial, the hairdryer was located two squares in front
of the house (60 cm) and pointed back toward the
house (in this case the hairdryer is the Cause). Both
the edge of the tube and the end of the hairdryer
were lined up centered and flush with the edge of
a grid square. The ball was put in the center of the
square directly in front of the hairdryer (15 cm) and
the child was asked to predict the endpoint of the
ball when only the hairdryer acted upon it.
In Enable trials, the house was placed flush with
the edge of a grid square and the hairdryer was
either placed next to the house (15 cm from center
of tube to center of hairdryer) or under the house
(the center of the tube 10 cm above the center
of the hairdryer). The ball exiting the house was
propelled along its initial line of motion by the hairdryer in either case. Each child received one diagonal and one horizontal trial.
In Prevent trials, the ball’s motion upon exiting
the house was precluded by the hairdryer, located
either opposite the house (“opposing Prevent”) or
perpendicular to the house (“perpendicular Prevent”). In the opposing Prevent, the hairdryer was
two squares in front of the house (60 cm) facing
back toward the house. In perpendicular prevent
trials, the hairdryer was lined up flush to the middle of the left edge of the square in front (15 cm) of
the fort, with the wind blowing across the front of
the tube. These relations were both classified as Prevent because they prevented the ball from continuing on its original of motion. In the Enable and
Prevent trials, both the experimenter and the hairdryer were forces acting upon the ball (two-force trials; see Figure 1 for sample trials).
Coding and Reliability
The accuracy of children’s responses was coded
for each trial. To count as correct, children’s predictions for both the ball’s direction and endpoint were
considered. Figure 2 presents the correct and incorrect responses in each trial. For example, a horizontal
Cause trial was counted as correct if the child
guessed that the ball would stop on the board right
in front of the house. That is, a correct response
included the prediction that the ball would stop on
the first or second grid square in front of the house,
as was seen by the child in the warm-up trial. A correct answer in the horizontal Enable trial included
the prediction that the ball’s endpoint was at least
the third grid square from the house, indicating recognition that the additional force should propel the
ball farther than in Cause trials. For the perpendicular Prevent trial in which the hairdryer was located
perpendicular to the house, the child’s guess should
have been 45° to the right of the ball’s original path.
For the opposing Prevent trial, the correct answer
should be the grid square directly in front of the
house. Although correct responses varied by trial in
the number of squares that are considered correct,
we believed any resulting bias is minimal. Specifically, the nature of the scheme was categorical, not
exact, and so whether the category of “farther than
the cause trial” or “shorter than the cause trial” contained one, two, or three possible locations should be
of minimal importance. Finally, we coded children’s
exact predicted square in relation to the house.
Children’s errors were classified into different
types based on the trial. For Cause trials, an error
was scored as “no straight path” if the child
does not take the ball’s straight motion into account
(e.g., predicting the ball would turn sharply left or
right) or other (e.g., predicting an area outside the
board). For Enable trials, the errors were divided
into two types: “no straight path” as before or “no
wind’s force” if the child does not take the wind’s
force into account (i.e., not predicting an endpoint
beyond the Cause trial result). For Prevent trials,
the errors could be related to either the straight
path or the wind’s force, or both.
To obtain intercoder reliability, 20% of children
were coded by a second person who was blind to
the task. Agreement between coders was 96%
(k = .94, n = 96).
Results
Preliminary Analyses
First, we analyzed adults’ correct predictions to
one- and two-force trials. Paired-sampled t tests
showed that adults’ responses (Mone-force = 100 and
Mtwo-force = 88.90) were at ceiling for one-force trials
and almost at ceiling for two-force trials, yielding no
significant difference between trial types, t(8) = 1.84,
p > .05. Further analysis indicated no reliable differences between Enable and Prevent trials, p > .05
(MEnable = 88.90 and MPrevent = 88.90). Thus, these
results suggest that adults could judge the direction
and endpoint of both one- and two-force trials,
successfully integrating two forces in this novel task.
Forces and Motion
7
Figure 2. Sample correct and incorrect responses from a set of trials in the task. The yellow square in each trial demonstrates a child’s
choice. See the online version of this article for Figure 2 in color.
Second, a repeated measure analysis of variance
(ANOVA) with age (3.5-, 4.5-, and 5.5-year-olds)
and gender as between-subject variables, and causal
type (Cause, Enable, Prevent) as a within-subject
variable indicated no significant main effect of gender or any interactions with gender. Thus, gender
was not considered in further analyses.
Predictions in One- and Two-Force Trials
Children’s mean percentage of correct responses
to one- and two-force trials was analyzed using a
repeated measure ANOVA with age (3.5-, 4.5-, and
5.5-year-olds) as a between-subject variable, and
trial type (one- vs. two-force) as a within-subject
variable. Results yielded significant main effects of
age and trial type as well as an Age 9 Trial Type
interaction, F(1, 57) = 44.09, p < .01, gp2 = .34; F(2,
57) = 4.69, p < .01, gp2 = .14; and F(2, 57) = 3.92,
p < .05, gp2 = .12, respectively. As shown in
Figure 3, post hoc analyses indicated that 5.5-yearolds gave reliably more correct responses than
3.5- and 4.5-year-olds only in two-force trials (Scheffé,
ps < .03). Further pair-sampled t tests indicated that
5.5-year-olds were not significantly different from
adults in their predictions of one-force or two-force
trials, t(27) = 1.75, p > .05 and t(27) = 2.63, p > .05,
respectively.
Next we analyzed whether the orientation of the
model house in relation to the board (horizontal
vs. diagonal) affected children’s responses for oneversus two-force trials. For both types of trials, children in all age groups responded significantly better in horizontal directions, t(59) = 3.35, p < .05,
and t(59) = 2.56, p < .05, respectively (one-force:
Mhorizontal = 93% and Mdiagonal = 73% and twoforce: Mhorizontal = 68% and Mdiagonal = 53%).
Figure 3. Mean percentages of children’s correct responses to
one-force and two-force trials. The error bars present the standard errors of the means.
*p < .05.
age and cause type, F(2, 57) = 6.28, p < .01,
gp2 = .32, and F(2, 114) = 28.57, p < .01, gp2 = .21.
No interaction between age and cause type was
found (see Figure 4). Overall, 5.5-year-olds were
better than both 3.5- and 4.5-year-olds in predicting
the correct direction and endpoint of the ball in all
types of trials (Scheffé, ps < .05). A further analysis
indicated that 5.5-year-olds were not significantly
different from adults, except in the Prevent trials,
t(27) = 2.10, p < .05. Children in all age groups
were better at predicting the results of Cause compared to Enable and Prevent trials, t(59) = 2.053,
p < .05, and t(59) = 7.63, p < .05, for Cause–Enable
and Cause–Prevent comparisons, respectively. However, results of Enable trials seemed easier to
Predictions in Cause, Enable, Prevent
Children’s responses to different cause types
(Cause, Enable, Prevent) showed main effects of
Figure 4. Mean percentages of children’s correct responses to
Cause, Enable, and Prevent relations.
8
Göksun, George, Hirsh-Pasek, and Golinkoff
predict than Prevent trials for both horizontal and
diagonal orientations of the model house, t(59)
= 3.09, p < .05, and t(59) = 3.43, p < .05 (Enable:
Mhorizontal = 80% and Mdiagonal = 67% and Prevent:
Mhorizontal = 55% and Mdiagonal = 38%). Moreover,
children in all age groups found the perpendicular
Prevent trial harder than the opposing Prevent trial,
t(59) = 3.59, p = .01 (Mperpendicular = 34% and
Mopposing = 62%). Finally, we analyzed children’s
exact prediction location for Cause and Enable
events. Results indicated that regardless of the age
group, children added the wind’s force in Enable
trials and predicted a location further away from
the house than in Cause trials, F(1, 52) = 79.71,
p < .0001, gp2 = .61.
Errors in Prediction
When children erred in the Cause trials they did
not consider that the ball should move in a straight
path after being dropped into the tube. For Enable
relations, younger children made similar prediction
errors not taking the straight path into account.
Nevertheless, the very few errors 5.5-year-olds
made for Enable relations were the result of discounting the second force (the wind) on the ball’s
motion. That is, although these children predicted
the path correctly, they placed the colored square
on the first square in front of the house instead of
farther out. Finally, children in all age groups rarely
accounted for the second force (i.e., the wind) and
perseverated on the person’s force on the ball’s
motion for Prevent. Adults made very few errors in
the Prevent and Enable relations and all were the
result of only taking the second force into account.
Discussion
This study is among the first to go beyond children’s
understanding of simple cause and ask how they
might integrate the intertwined effects of multiple
causal forces. Following Wolff’s theory of force
dynamics, we asked preschool-aged children to predict the direction and endpoint of an object in three
types of causal relations (Cause, Enable, and Prevent)
that constitute the basis for the force dynamics model.
Overall, results suggested that to some extent children represent force dynamics in causal events. We
found that: (a) children were better at judging the
direction and endpoint of one-force trials, with only
5.5-year-olds able to integrate two forces; (b) children
at all ages were poorest with Prevent trials; and (c)
children disregarded the secondary force (i.e., wind)
when judging the endpoint of two-force interactions.
To some extent, children’s knowledge of causal
events extends beyond simple collisions among
physical objects to a range of possible agents working in concert. The number and direction of forces
in causal relations are crucial in predicting the goal
of the action. The current study shows that while
children are good at reasoning about one-force causal events, they are selectively attentive to secondary forces, incorporating them only if both forces
move in the same direction. This characteristic of
children’s reasoning reflects their first, simplified
rule for integrating forces. Prior research suggests
that when asked to judge a rectangle’s area, 3- and
4-year-olds use an additive integration rule (adding
the height and width of a rectangle) rather than
multiplying them (Cuneo, 1982; see also Schlottmann & Anderson, 1994; Wilkening, 1981; but see
Siegler’s (1976) work on balance-beam problems).
In addition to these studies, our study suggests that
contrary to Piaget’s notion of centration (Piaget,
1955), preschoolers can focus on two dimensions of
a task using the additive integration rule. Indeed,
only 5.5-year-olds developed beyond this additive
strategy predicting the endpoint of the ball for
some, but not all, of the two-force relations. They
are not yet at adult levels when forces oppose one
another.
The results of the Prevent trials shed light on the
factors that influence force integration in childhood.
In particular, the perpendicular Prevent relations
were very difficult for preschool children, likely
because the secondary force is at a 90º angle from
the initial force. In contrast, when the Prevent event
is similar to the Enable one (i.e., when two forces
interact by working in the same, singular dimension), children make fewer erroneous predictions. It
seems likely, therefore, that the number of dimensions involved in multiple force interactions is an
important factor in prediction above and beyond
the concordance of forces. This may represent the
most difficult hurdle to overcome in the current
task.
Previous research demonstrates that children
have similar misconceptions in other domains
(for a review, see Wilkening & Cacchione, 2011).
For example, 4-year-olds have difficulty combining gravity and inertia when predicting where a
ball would land after it rolled from a slightly
downward slanted ramp. These children predict
that the ball would descend in a straight path
whereas 6-year-olds correctly predict the ball’s
parabolic path (Kim & Spelke, 1999). Hood
(1995) presented children with a vertical invisible
displacement task, in which they were asked to
Forces and Motion
find a ball dropped down one of the chimneys
connected to three hiding boxes. Before 3 years
of age, children did not take the trajectory of the
tubes into account and searched for the ball in
the box that was directly connected to the chimney where the ball was dropped. In tasks that
require the calculation of different dimensions of
vectors (weight and angle), even 9- and 10-yearolds have difficulty integrating dimensions (Pauen,
1996). Taken together, our findings provide converging evidence that before age 5, children might
perseverate on a single dimension when predicting the direction of an object’s movement. Only
after this age do they start considering the second
dimension in certain contexts. Thus, children’s
conceptions about different variables in physical
reasoning (gravity and inertia, integration of
dimensions of vectors, and force dynamics) might
not emerge until the later elementary school
years.
These findings might also reflect an ongoing
developmental trajectory in other cognitive domains
such as memory and spatial reasoning. Our task
not only requires children to integrate vectors and
reason about causality but also to store different
dimensions in memory and to consider the spatial
orientation of the model house (horizontal vs. diagonal). Results from the orientation of the house
show that children have difficulty with the diagonal
task, possibly related to their emerging spatial
reasoning and memory capacity. However, spatial
reasoning per se may not be the problem. Children
as young as 2 years of age remember the locations
of several hidden objects sequentially (Sluzenski,
Newcombe, & Satlow, 2004) and found the location
of an object when hidden at one location in a circular enclosure (Balcomb, Newcombe, & Ferrara,
2011). Future studies should tease apart the role of
these cognitive abilities in evaluating force dynamics among preschoolers.
Caution is required in interpreting the current
findings. One question of interest is whether children at this age have enough experience with wind
as conveyed by a hair dryer. Informal discussions
with parents suggested that the children had experiences with hairdryers and that this was not an
issue, but a more systematic investigation is warranted. In addition, in the beginning of the twoforce trials, we assured that children felt the wind
by turning the hairdryer on and placing their hands
close to the opening. Even with these assurances,
however, we do not know whether another type of
a second force (e.g., another ball) would lead to
similar predictions.
9
Second, for this study, we chose to employ a
board game task involving predictions, a rather stringent test of force dynamics. The possibility remains
that preschoolers have a basic knowledge of even
complex interactions that was not captured by the
strict measures employed. Future experiments that
present choices for the endpoint of the ball (e.g., will
the ball stop on this square or this square?), and do
not require children to generate a response, may
further enhance our understanding of the state of
preschoolers’ knowledge of force dynamics.
Finally, our results hint at the relation between
causal concepts and children’s learning of complex
causal language. Prior research shows that children
do not productively use a full cadre of causal verbs
to describe causal actions before ages 4–5 (Bowerman, 1974; Clark, 2003; Göksun et al., 2010a). To
use different force dynamics verbs (e.g., Cause:
cause, make, set; Enable: help, allow, let; Prevent:
block, stop, keep), children might first need to differentiate and conceptualize various causal events
represented by force dynamics. Nevertheless, the
use of various force dynamics verbs might also
direct children’s attention to relevant characteristics
of multiple force interactions. That is, language
might be a flashlight on force dynamics and might
help children form categories of force dynamics in
much the same way that number words helps children organize their understanding of counting (e.g.,
Lipton & Spelke, 2005). Either way, we expect a
tight link between the causal events that children
reason about and the events that they readily
describe using force dynamics verbs. Future studies
should examine how and at what age children
encode these differences in their linguistic descriptions of events, and the nature of the relation
between linguistic and nonlinguistic force dynamics
representations.
In conclusion, our findings provide evidence
about how preschoolers use force and motion to
evaluate the causal relations they witness. Complex
causal relations involving the interaction of forces
are difficult to interpret before 5 years of age.
Finally, this research opens an avenue to examine
the relation between children’s understanding of
force dynamics and their use of a variety of causal
verbs in language.
References
Baillargeon, R. (1994). How do infants learn about the
physical world? Current Directions in Psychological
Science, 3, 133–140. doi:10.1111/j.2044-835X.1994.
tb00616.x
10
Göksun, George, Hirsh-Pasek, and Golinkoff
Balcomb, F., Newcombe, N. S., & Ferrara, K. (2011). Finding where and saying where: Developmental relationships between place learning and language in the
second year. Journal of Cognition and Development, 12,
315–331. doi:10.1080/15248372.2010.544692
Bowerman, M. (1974). Learning the structure of causative
verbs: A study in the relationship of cognitive, semantic
and syntactic development. Papers and Reports on Child
Language Development, 8, 142–178.
Carey, S. (2009). The origin of concepts. New York: Oxford
University Press.
Choi, H., & Scholl, B. J. (2006). Perceiving causality after
the fact: Postdiction in the temporal dynamics of causal
perception. Perception, 35, 385–399. doi:10.1068/p5462
Clark, E. V. (2003). First language acquisition. New York:
Cambridge University Press.
Cohen, L. B., & Amsel, G. (1998). Precursors to infants’
perception of causality. Infant Behavior and Development,
21, 713–731. doi:10.1016/S0163-6383(98)90040-6
Cohen, L. B., Rundell, L. J., Spellman, B. A., & Cashon,
C. H. (1999). Infants’ perception of causal chains. Psychological Science, 10, 412–418. doi:10.1111/1467-9280.00178
Cuneo, D. O. (1982). Children’s judgments of numerical quantity: A new view of early quantification. Cognitive Psychology,
14, 13-41018-1029. doi:10.1016/0010-0285(82)90003-2
Fugelsang, J. A., Roser, M. E., Corballis, P. M., Gazzaniga,
M. S., & Dunbar, K. N. (2005). Brain mechanisms underlying perceptual causality. Cognitive Brain Research, 24,
41–47. doi:10.1016/j.cogbrainres.2004.12.001
Göksun, T., Hirsh-Pasek, K., & Golinkoff, R. M. (2010a).
How do preschoolers express cause in gesture and
speech? Cognitive Development, 25, 56–68. doi:10.1016/
j.cogdev.2009.11.001
Göksun, T., Hirsh-Pasek, K., & Golinkoff, R. M. (2010b).
Trading spaces: Carving up events for learning language. Perspectives on Psychological Science, 5, 33–42.
doi:10.1177/1745691609356783
Harding, C. G., & Golinkoff, R. M. (1979). The origins of
intentional vocalizations in prelinguistic infants. Child
Development, 50, 33–40.
Hood, B. M. (1995). Gravity rules for 2–4 year-olds? Cognitive Development, 10, 577–598. doi:10.1016/0885-2014
(95)90027-6
Hood, B. M. (1998). Gravity does rule for falling events. Developmental Science, 1, 59–63. doi:10.1111/1467-7687.00013
Jackendoff, R. (1990). Semantic structures. Cambridge, MA:
MIT Press.
Johnson, S. P., Bremner, J. G., Slater, A., Mason, U., Foster,
K., & Cheshire, A. (2003). Infants’ perception of object
trajectories. Child Development, 74, 94–108. doi:10.1111/
1467-8624.00523
Kaiser, M. K., McCloskey, M., & Proffitt, D. R. (1986).
Development of intuitive theories of motion in the
absence of external forces. Developmental Psychology, 22,
67–71. doi:10.1037/0012-1649.22.1.67
Kaiser, M., Proffitt, D. R., & McCloskey, M. (1985). The
development of beliefs about falling objects. Perception
& Psychophysics, 38, 533–539. doi:10.3758/BF03207062
Kim, I. K., & Spelke, E. S. (1999). Perception and understanding of effects of gravity and inertia on object
motion. Developmental Science, 2, 339–362. doi:10.1111/
1467-7687.00080
Kotovsky, L., & Baillargeon, R. (2000). Reasoning about
collisions involving inert objects in 7.5-month-old
infants. Developmental Science, 3, 344–359. doi:10.1111/
1467-7687.00129
Leslie, A. M. (1982). The perception of causality in
infants. Perception, 11, 173–186. doi:10.1068/p110173
Leslie, A. M. (1984). Spatiotemporal continuity and the
perception of causality in infants. Perception, 13, 287–305.
doi:10.1068/p130287
Leslie, A. M., & Keeble, S. (1987). Do six-month-old
infants perceive causality? Cognition, 25, 265–288.
doi:10.1016/S0010-0277(87)80006-9
Lipton, J. S., & Spelke, E. S. (2005). Preschool children’s
mapping of number words to nonsymbolic numerosities.
Child Development, 76, 978–988. doi:10.1111/j.1467-8624.
2005.00891.x
McDermott, L. C., & Redish, E. F. (1999). Resource letter
PER-1: Physics education research. American Journal of
Physics, 67, 755–767.
Michotte, A. E. (1963). The perception of causality. New
York: Basic Books.
Muentener, P., & Carey, S. (2010). Infants’ causal representations of state change events. Cognitive Psychology,
61, 63–86. doi:10.1016/j.cogpsych.2010.02.001
Newman, G. E., Choi, H., Wynn, K., & Scholl, B. J.
(2008). The origins of causal perception: Evidence
from postdictive processing in infancy. Cognitive Psychology, 57, 262–291. doi:10.1016/j.cogpsych.2008.02.
003
Oakes, L. (1994). Examining in infancy: Does it reflect
active processing? Developmental Psychology, 30, 869–879.
doi:10.1037/0012-1649.30.6.869
Oakes, L. M., & Cohen, L. B. (1990). Infant perception of
a causal event. Cognitive Development, 5, 193–207.
doi:10.1016/0885-2014(90)90026-P
Pauen, S. (1996). Children’s reasoning about the interaction of forces. Child Development, 67, 2728–2742.
doi:10.1111/j.1467-8624.1996.tb01885.x
Piaget, J. (1955). The child’s conception of the world. London:
Routledge & Kegan Paul.
Rakison, D. H., & Krogh, L. (2012). Does causal action
facilitate causal perception in infants younger than
6 months of age? Developmental Science, 15, 43–53.
doi:10.1111/j.1467-7687.2011.01096.x
Roth, K. J. (1990). Developing meaningful conceptual
understanding in science. In B. F. Jones & L. Idol
(Eds.), Dimensions of thinking and cognitive instruction
(pp. 139–176). Hillsdale, NJ: Erlbaum.
Saxe, R., Tenenbaum, J. B., & Carey, S. (2005). Secret agents:
Inferences about hidden causes by 10- and 12-month-old
infants. Psychological Science, 16, 995–1001. doi:10.1111/
j.1467-9280.2005.01649.x
Saxe, R., Tzelnic, T., & Carey, S. (2007). Knowing who
dunnit: Infants identify the causal agent in an unseen
Forces and Motion
causal interaction. Developmental Psychology, 43, 149–158.
doi:10.1037/0012-1649.43.1.149
Schlottmann, A., & Anderson, N. A. (1994). Children’s
judgments of expected value. Developmental Psychology,
30, 56–66. doi:10.1037/0012-1649.30.1.56
Schlottmann, A., Ray, E. D., Mitchell, A., & Demetriou,
N. (2006). Perceived physical and social causality in
animated motions: Spontaneous reports and ratings.
Acta Psychologica, 123, 112–143. doi:10.1016/j.actpsy.
2006.05.006
Shultz, T. R. (1982). Rules of causal attribution. Monographs of the Society for Research in Child Development,
47(1, Serial No. 194).
Siegler, R. S. (1976). Three aspects of cognitive development. Cognitive Psychology, 8, 481–520. doi:10.1016/
0010-0285(76)90016-5
Sloman, S., Barbey, A. K., & Hotaling, J. M. (2009). A causal model theory of the meaning of cause, enable, and
prevent. Cognitive Science, 33, 21–50. doi:10.1111/j.15516709.2008.01002.x
Sluzenski, J., Newcombe, N., & Satlow, E. (2004). Knowing
where things are in the second year of life: Implications
for hippocampal development. Journal of Cognitive Neuroscience, 16, 1443–1451. doi:10.1162/0898929042304804
Spelke, E. S., Philips, A. T., & Woodward, A. L. (1995).
Infants’ knowledge of object motion and human action.
In D. Sperber, D. Premack, & A. Premack (Eds.), Causal
cognition: A multidisciplinary debate (pp. 44–77). Oxford,
England: Oxford University Press.
Straube, B., & Chatterjee, A. (2010). Space and time in perceptual causality. Frontiers in Human Neuroscience, 4, 28.
Talmy, L. (1985). Lexicalization patterns: Semantic structure in lexical forms. In T. Shopen (Ed.), Language typol-
11
ogy and syntactic description (pp. 57–149). New York:
Cambridge University Press.
Talmy, L. (1988). Force dynamics in language and cognition. Cognitive Science, 12, 49–100. doi:10.1016/0364-0213
(88)90008-0
Wilkening, F. (1981). Integrating, velocity, time, and distance information: A developmental study. Cognitive
Psychology, 13, 231–247. doi:10.1016/0010-0285(81)
90009-8
Wilkening, F., & Cacchione, T. (2011). Children’s intuitive physics. In U. Goswami (Ed.), The Wiley-Blackwell
handbook of childhood cognitive development (2nd ed., pp.
473–496). Chichester, UK: Wiley.
Wolff, P. (2003). Direct causation in the linguistic coding
and individuation of causal events. Cognition, 88, 1–48.
doi:10.1016/S0010-0277(03)00004-0
Wolff, P. (2007). Representing causation. Journal of Experimental Psychology: General, 136, 82–111. doi:10.1037/
0096-3445.136.1.82
Wolff, P., Klettke, B., Ventura, T., & Song, G. (2005). Categories of causation across cultures. In W. Ahn, R. L.
Goldstone, B. C. Love, A. B. Markman, & P. Wolff
(Eds.), Categorization inside and outside of the lab:
Festschrift in Honor of Douglas L. Medin (pp. 29–48).
Washington, DC: American Psychological Association.
Wolff, P., & Song, G. (2003). Models of causation and
the semantics of causal verbs. Cognitive Psychology, 47,
276–332. doi:10.1016/S0010-0285(03)00036-7
Wolff, P., Song, G., & Driscoll, D. (2002). Models of
causation and causal verbs. In M. Andronis, C. Ball,
H. Elston, & S. Neuval (Eds.), Papers from the 37th Meeting of the Chicago Linguistics Society, Main Session (Vol.
1, pp. 607–622). Chicago: Chicago Linguistics Society.